Are there laws of genome evolution?

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection, therefore the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as 'laws of evolutionary genomics' in the same sense 'law' is understood in modern physics.Comment: 17 pages, 2 figure

The significance of genome-wide transcriptional regulation in the evolution of stress tolerance.

It is widely recognized that stress plays an important role in directing the adaptive adjustment of an organism to changing environments. However, very little is known about the evolution of mechanisms that promote stress-induced variation. Adaptive transcriptional responses have been implicated in the evolution of tolerance to natural and anthropogenic stressors in the environment. Recent technological advances in transcriptomics provide a mechanistic understanding of biological pathways or processes involved in stress-induced phenotypic change. Furthermore, these studies are (semi) quantitative and provide insight into the reaction norms of identified target genes in response to specific stressors. We argue that plasticity in gene expression reaction norms may be important in the evolution of stress tolerance and adaptation to environmental stress. This review highlights the consequences of transcriptional plasticity of stress responses within a single generation and concludes that gene promoters containing a TATA box are more capable of rapid and variable responses than TATA-less genes. In addition, the consequences of plastic transcriptional responses to stress over multiple generations are discussed. Based on examples from the literature, we show that constitutive over expression of specific stress response genes results in stress adapted phenotypes. However, organisms with an innate capacity to buffer stress display plastic transcriptional responses. Finally, we call for an improved integration of the concept of phenotypic plasticity with studies that focus on the regulation of transcription. © Springer Science+Business Media B.V. 2010

Identification of ncRNAs as Potential Therapeutic Targets in Multiple Sclerosis Through Differential ncRNA – mRNA Network Analysis

Background: Several studies have revealed a potential role for both small nucleolar RNAs (snoRNAs) and microRNAs (miRNAs) in the physiopathology of relapsing-remitting multiple sclerosis (RRMS). This potential implication has been mainly described through differential expression studies. However, it has been suggested that, in order to extract additional information from large-scale expression experiments, differential expression studies must be complemented with differential network studies. Thus, the present work is aimed at the identification of potential therapeutic ncRNA targets for RRMS through differential network analysis of ncRNA - mRNA coexpression networks. ncRNA - mRNA coexpression networks have been constructed from both selected ncRNA (specifically miRNAs, snoRNAs and sdRNAs) and mRNA large-scale expression data obtained from 22 patients in relapse, the same 22 patients in remission and 22 healthy controls. Condition-specific (relapse, remission and healthy) networks have been built and compared to identify the parts of the system most affected by perturbation and aid the identification of potential therapeutic targets among the ncRNAs. Results: All the coexpression networks we built present a scale-free topology and many snoRNAs are shown to have a prominent role in their architecture. The differential network analysis (relapse vs. remission vs. controls' networks) has revealed that, although both network topology and the majority of the genes are maintained, few ncRNA - mRNA links appear in more than one network. We have selected as potential therapeutic targets the ncRNAs that appear in the disease-specific network and were found to be differentially expressed in a previous study. Conclusions: Our results suggest that the diseased state of RRMS has a strong impact on the ncRNA - mRNA network of peripheral blood leukocytes, as a massive rewiring of the network happens between conditions. Our findings also indicate that the role snoRNAs have in targeted gene silencing is a widespread phenomenon. Finally, among the potential therapeutic target ncRNAs, SNORA40 seems to be the most promising candidate.This work has been supported partially by Fondo de investigacion Sanitaria from Instituto Carlos III through the project FIS PS09/02105, by SAIOTEK (SAIO11-PC11BN003) and by the Spanish Net of Multiple Sclerosis. HI and MMC has been supported by departamento de educacion del Gobierno Vasco through a PhD grant

Statistics and Evolution of Functional Genomic Sequence

In this thesis, three separate problems of genomics are addressed, utilizing methods related to the field of statistical mechanics. The goal of the project discussed in the first chapter is the elucidation of post-transcriptional gene regulation imposed by microRNAs, a recently discovered class of tiny non-coding RNAs. A probabilistic algorithm for the computational identification of genes regulated by microRNAs is introduced, which was developed based on experimental data and statistical analysis of whole genome data. In particular, the application of this algorithm to multiple-alignments of groups of related species allows for the specific and sensitive detection of genes targeted by microRNAs on a genome-wide level. Examination of clade-specific predictions and cross-clade comparison yields deeper insights into microRNA biology and first clues about long-term evolution of microRNA regulation, which are discussed in detail. Modeling evolutionary dynamics of microsatellites, an abundant class of repetitive sequence in eukaryotic genomes, was the objective of the second project and is discussed in chapter two. Inspired by the putative functionality of some of these elements and the difficulty of constructing correct sequence alignments that reflect the evolutionary relationships between microsatellites, a neutral model for microsatellite evolution is developed and tested in the fruit fly Drosophila melanogaster by comparing evolutionary rates predicted by the model to independent measurements of these rates from multiple alignments of three closely relates Drosophila species. The model is applied separately to genomic sequence categories of different functional annotations in order to assess the varying influence of selective constraint among these categories. In the last chapter, a general population genetic model is introduced that allows for the determination of transcription factor binding site stability as a function of selection strength, mutation rate and effective population size at arbitrary values of these parameters. The analytical solution of this model indicates the probability of a binding site to be functional. The model is used to compute the population fraction of functional binding sites at fixed selection pressure across a variety of different taxa. The results lead to the conclusion that a decreasing effective population size, such as observed at the evolutionary transition from prokaryotes to eukaryotes, could result in loss of binding site stability. An extension to our model serves us to assess the compensatory effect of the emergence of multiple binding sites for the same transcription factor in order to maintain the existing regulatory relationship

Investigating 3D genome organisation in Caenorhabditis elegans with Accessible Region Conformation Capture (ARC-C)

3C and its derivatives have been applied in various organisms to study chromatin architecture. However, these methods have limitations: most of them are limited to restriction-fragment resolution and all of them, with the exception of Hi-C, only survey a pre-defined subset of the genome. I developed a variant of Hi-C, named Accessible Region Conformation Capture (ARC-C), in C. elegans, which interrogates genome organisation at multiple scales genome-wide - from domains and compartments to high resolution interactions between regulatory elements. I applied ARC-C in wild-type Bristol N2, met-2 set-25 mutants that have no H3K9 methylation to study the effects on domain and compartment formation. In these mutants, compartmentalisation (i.e. inter-domain interactions) between H3K27me3-enriched regulated domains is reduced. I also used ARC-C in blmp-1 mutants to understand the role of BLMP-1 in chromatin looping. In blmp-1 mutants, interactions between putative BLMP-1 mediated loops for downregulated genes are significantly reduced. In wild-type worms, when surveying significant interactions at 500 bp resolution, I observe the presence of dense clusters of significant interactions anchored at high occupancy target (HOT) regions that I call “hubs.” Interestingly, the deletion of these hubs does not affect the transcription of linked or local genes. However, local interactions are altered and some extent of redundancy is observed. To improve our ARC-C protocol, I tested several variations with different enzymes and biotin-mediated streptavidin beads pulldown. In all, ARC-C revealed insights into genome organisation in C. elegans and I have made progress toward a next-generation version of the method.A*STAR National Science Scholarship (PhD

Systems-Based Analysis of the \u3cem\u3eSarcocystis neurona\u3c/em\u3e Genome Identifies Pathways That Contribute to a Heteroxenous Life Cycle

Sarcocystis neurona is a member of the coccidia, a clade of single-celled parasites of medical and veterinary importance including Eimeria, Sarcocystis, Neospora, and Toxoplasma. Unlike Eimeria, a single-host enteric pathogen, Sarcocystis, Neospora, and Toxoplasma are two-host parasites that infect and produce infectious tissue cysts in a wide range of intermediate hosts. As a genus, Sarcocystis is one of the most successful protozoan parasites; all vertebrates, including birds, reptiles, fish, and mammals are hosts to at least one Sarcocystis species. Here we sequenced Sarcocystis neurona, the causal agent of fatal equine protozoal myeloencephalitis. The S. neurona genome is 127 Mbp, more than twice the size of other sequenced coccidian genomes. Comparative analyses identified conservation of the invasion machinery among the coccidia. However, many dense-granule and rhoptry kinase genes, responsible for altering host effector pathways in Toxoplasma and Neospora, are absent from S. neurona. Further, S. neurona has a divergent repertoire of SRS proteins, previously implicated in tissue cyst formation in Toxoplasma. Systems-based analyses identified a series of metabolic innovations, including the ability to exploit alternative sources of energy. Finally, we present an S. neurona model detailing conserved molecular innovations that promote the transition from a purely enteric lifestyle (Eimeria) to a heteroxenous parasite capable of infecting a wide range of intermediate hosts. IMPORTANCE Sarcocystis neurona is a member of the coccidia, a clade of single-celled apicomplexan parasites responsible for major economic and health care burdens worldwide. A cousin of Plasmodium, Cryptosporidium, Theileria, and Eimeria, Sarcocystis is one of the most successful parasite genera; it is capable of infecting all vertebrates (fish, reptiles, birds, and mammals—including humans). The past decade has witnessed an increasing number of human outbreaks of clinical significance associated with acute sarcocystosis. Among Sarcocystis species, S. neurona has a wide host range and causes fatal encephalitis in horses, marine mammals, and several other mammals. To provide insights into the transition from a purely enteric parasite (e.g., Eimeria) to one that forms tissue cysts (Toxoplasma), we present the first genome sequence of S. neurona. Comparisons with other coccidian genomes highlight the molecular innovations that drive its distinct life cycle strategies

High specificity in the C. elegans innate immune responses

In the past decade, the paradigm which claimed that invertebrate immune systems lack specificity has been reconsidered. Accumulating evidence supports that invertebrate immune systems are able to mount specific responses to the pathogen species-, and even to the pathogen strain-level. However, the underlying molecular mechanisms behind invertebrate immune specificity remain mostly unknown. We chose to study the mechanisms of specific immune responses of the worm to two different pathogenic strains of the Gram-positive bacterium Bacillus thuringiensis (MYBY18247 and MYBT18679), because there is phenotypic evidence of specific genotype-genotype interactions between this host-pathogen pair. We did an initial RNA-Seq experiment upon pathogen exposure and found that 9% of the differentially expressed genes change their expression in different ways when comparing the two pathogen strains. Through promoter region motif enrichment analysis, we found the GATA transcription factor ELT-2 is responsible for the pathogen strain-specific transcriptomic response. Upon elt-2 knockdown worms exposed to MYBT18679 display lower survival rate coupled with higher intestinal damage than non-infected controls. Additionally, by performing further genetic analysis using gene knockdown and knockout, we found that the p38 MAPK pathway acts likely in parallel to elt-2 and the transcription factor skn-1 cooperates with elt-2 to promote resistance to MYBT18679. On the other hand, elt-2 knockdown leads to a substantially higher survival rate, together with lower intestinal tissue damage compared to control worms, upon exposure to MYBT18247, another pathogenic Bacillus thuringiensis strain. The MYBT18247 pathogen load of elt-2(RNAi) worms compared to control worms remained unchanged, suggesting the elt-2 negatively regulates tolerance towards MYBT18247. We conclude that ELT-2 coordinates strain-specific immune responses in this invertebrate host and promotes resistance upon exposure to MYBT18679, while it negatively regulates tolerance to MYBT18247

The Structure of a Gene Co-Expression Network Reveals Biological Functions Underlying eQTLs

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology